Bi-allelic variants in COQ8B, a gene involved in the biosynthesis of coenzyme Q10, lead to non-syndromic retinitis pigmentosa.

Retinitis pigmentosa (RP) is a Mendelian disease characterized by gradual loss of vision, due to the progressive degeneration of retinal cells. Genetically, it is highly heterogeneous, with pathogenic variants identified in more than 100 genes so far. Following a large-scale sequencing screening, we identified five individuals (four families) with recessive and non-syndromic RP, carrying as well bi-allelic DNA changes in COQ8B, a gene involved in the biosynthesis of coenzyme Q10. Specifically, we detected compound heterozygous assortments of five disease-causing variants (c.187C>T [p.Arg63Trp], c.566G>A [p.Trp189Ter], c.1156G>A [p.Asp386Asn], c.1324G>A [p.Val442Met], and c.1560G>A [p.Trp520Ter]), all segregating with disease according to a recessive pattern of inheritance. Cell-based analysis of recombinant proteins deriving from these genotypes, performed by target engagement assays, showed in all cases a significant decrease in ligand-protein interaction compared to the wild type. Our results indicate that variants in COQ8B lead to recessive non-syndromic RP, possibly by impairing the biosynthesis of coenzyme Q10, a key component of oxidative phosphorylation in the mitochondria.

Monogenic causes of cerebral small vessel disease and stroke.

Cerebral small vessel disease (cSVDs) account for 25% of stroke and are a frequent cause of cognitive or motor disability in adults. In a small number of patients, cSVDs result from monogenic diseases, the most frequent being cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). An early disease onset, a suggestive family history, and a low vascular risk profile contrasting with a high load of cSVD imaging markers represent red flags that must trigger molecular screening. To date, a dozen of genes is involved in Mendelian cSVDs, most of them are responsible for autosomal dominant conditions of variable penetrance. Some of these mendelian cSVDs (CADASIL, HTRA1-related cSVD, pontine autosomal dominant microangiopathy and leukoencephalopathy (PADMAL), cathepsin-A related arteriopathy with strokes and leukoencephalopathy (CARASAL), and cSVD related to LAMB1 mutations) are causing ischemic stroke. Others (COL4A1/COL4A2-related angiopathy and hereditary cerebral amyloid angiopathy) preferentially lead to intracerebral hemorrhages. The clinical features of different Mendelian cSVDs can overlap. Therefore, the current approach is based on simultaneous screening of all genes involved in these conditions through a panel-targeted sequencing gene or exome sequencing. Nevertheless, a pathogenic variant is identified in less than 15% of patients with a suspected genetic cerebrovascular disease, suggesting that many additional genes remain to be identified.

A Copernican revolution of multigenic analysis: A retrospective study on clinical exome sequencing in unclear genetic disorders.

Despite the inevitable shift in medical practice towards a deeper understanding of disease etiology and progression through multigenic analysis, the profound historical impact of Mendelian diseases cannot be overlooked. These diseases, such as cystic fibrosis and thalassemia, are characterized by a single variant in a single gene leading to clinical conditions, and have significantly shaped our medical knowledge and treatments. In this respect, the monogenic approach inevitably results in the underutilization of Next-Generation Sequencing (NGS) data. Herein, a retrospective study was performed to assess the diagnostic value of the clinical exome in 32 probands with specific phenotypic characteristics (patients with autoinflammation and immunological dysregulation, N = 20; patients diagnosed with Hemolytic uremic syndrome N = 9; and patients with Waldenström macroglobulinemia, N = 3). A gene enrichment analysis was performed using the *. VCF file generated by SOPHiA-DDM-v4. This analysis selected a subset of genes containing pathogenic or likely pathogenic variants with autosomal dominant (AD) inheritance. In addition, all variants of uncertain significance (VUS) were included, filtered by AD inheritance mode, the presence of compound heterozygotes, and a minor allele frequency (MAF) cutoff of 0.05 %. The aim of the pipeline described here is based on a perspective shift that focuses on analyzing patients' gene assets, offering new light on the complex interplay between genetics and disease presentation. Integrating this approach into clinical practices could significantly enhance the management of patients with rare genetic disorders.

Inverted triplications formed by iterative template switches generate structural variant diversity at genomic disorder loci.

The duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a complex genomic rearrangement (CGR). Although it has been identified as an important pathogenic DNA mutation signature in genomic disorders and cancer genomes, its architecture remains unresolved. Here, we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the DNA of 24 patients identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted structural variant (SV) haplotypes. Using a combination of short-read genome sequencing (GS), long-read GS, optical genome mapping, and single-cell DNA template strand sequencing (strand-seq), the haplotype structure was resolved in 18 samples. The point of template switching in 4 samples was shown to be a segment of ∼2.2-5.5 kb of 100% nucleotide similarity within inverted repeat pairs. These data provide experimental evidence that inverted low-copy repeats act as recombinant substrates. This type of CGR can result in multiple conformers generating diverse SV haplotypes in susceptible dosage-sensitive loci.

PHACTboost: A Phylogeny-Aware Pathogenicity Predictor for Missense Mutations via Boosting.

Most algorithms that are used to predict the effects of variants rely on evolutionary conservation. However, a majority of such techniques compute evolutionary conservation by solely using the alignment of multiple sequences while overlooking the evolutionary context of substitution events. We had introduced PHACT, a scoring-based pathogenicity predictor for missense mutations that can leverage phylogenetic trees, in our previous study. By building on this foundation, we now propose PHACTboost, a gradient boosting tree-based classifier that combines PHACT scores with information from multiple sequence alignments, phylogenetic trees, and ancestral reconstruction. By learning from data, PHACTboost outperforms PHACT. Furthermore, the results of comprehensive experiments on carefully constructed sets of variants demonstrated that PHACTboost can outperform 40 prevalent pathogenicity predictors reported in the dbNSFP, including conventional tools, metapredictors, and deep learning-based approaches as well as more recent tools such as AlphaMissense, EVE, and CPT-1. The superiority of PHACTboost over these methods was particularly evident in case of hard variants for which different pathogenicity predictors offered conflicting results. We provide predictions of 215 million amino acid alterations over 20,191 proteins. PHACTboost is available at https://github.com/CompGenomeLab/PHACTboost. PHACTboost can improve our understanding of genetic diseases and facilitate more accurate diagnoses.

Monogenic Kidney Diseases in Kidney Transplantation.

Monogenic kidney diseases are involved in up to 15% of end-stage kidney diseases (ESKDs) in adults, and in 70 % of pediatric patients. When these disorders lead to kidney failure (KF), kidney transplantation (KT) is the preferred mode of replacement therapy. KT requires specific considerations depending on the nature of the genetic disorder, the potential oncological risk, the risk of recurrence in the graft, the possibility of specific complications of immunosuppression, and the issue of living donation. The availability of genetic testing should play an increasing role in the evaluation of patients or related living donor candidates before transplantation, relevant for the pretransplantation and posttransplantation management.

Affected cell types for hundreds of Mendelian diseases revealed by analysis of human and mouse single-cell data.

Mendelian diseases tend to manifest clinically in certain tissues, yet their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in Mendelian diseases. Overall, we inferred the likely affected cell types for 328 diseases. We corroborated our findings by literature text-mining, expert validation, and recapitulation in mouse corresponding tissues. Based on these findings, we explored characteristics of disease-affected cell types, showed that diseases manifesting in multiple tissues tend to affect similar cell types, and highlighted cases where gene functions could be used to refine inference. Together, these findings expand the molecular understanding of disease mechanisms and cellular vulnerability.

Identification of Rare Variants Involved in High Myopia Unraveled by Whole Genome Sequencing.

Purpose: Myopia (nearsightedness) is a condition in which a refractive error (RE) affects vision. Although common variants explain part of the genetic predisposition (18%), most of the estimated 70% heritability is missing. Here, we investigate the contribution of rare genetic variation because this might explain more of the missing heritability in the more severe forms of myopia. In particular, high myopia can lead to blindness and has a tremendous impact on a patient and at the societal level. The exact molecular mechanisms behind this condition are not yet completely unraveled, but whole genome sequencing (WGS) studies have the potential to identify novel (rare) disease genes, explaining the high heritability. Design: Cross-sectional study performed in the Netherlands. Participants: We investigated 159 European patients with high myopia (RE > -10 diopters). Methods: We performed WGS using a stepwise filtering approach and burden analysis. The contribution of common variants was calculated as a genetic risk score (GRS). Main Outcome Measures: Rare variant burden, GRS. Results: In 25% (n = 40) of these patients, there was a high (> 75th percentile) contribution of common predisposing variants; that is, these participants had higher GRSs. In 7 of the remaining 119 patients (6%), deleterious variants in genes associated with known (ocular) disorders, such as retinal dystrophy disease (prominin 1 [PROM1]) or ocular development (ATP binding cassette subfamily B member 6 [ABCB6], TGFB induced factor homeobox 1 [TGIF1]), were identified. Furthermore, without using a gene panel, we identified a high burden of rare variants in 8 novel genes associated with myopia. The genes heparan sulfate 6-O-sulfotransferase 1 (HS6ST1) (proportion in study population vs. the Genome Aggregation Database (GnomAD) 0.14 vs. 0.03, P = 4.22E-17), RNA binding motif protein 20 (RBM20) (0.15 vs. 0.06, P = 4.98E-05), and MAP7 domain containing 1 (MAP7D1) (0.19 vs. 0.06, P = 1.16E-10) were involved in the Wnt signaling cascade, melatonin degradation, and ocular development and showed most biologically plausible associations. Conclusions: We found different contributions of common and rare variants in low and high grade myopia. Using WGS, we identified some interesting candidate genes that could explain the high myopia phenotype in some patients. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Exome/Genome Sequencing in Undiagnosed Syndromes.

Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.

Ophthalmic genetic counselling: emerging trends in practice perspectives in Asia.

Genetic counselling (GC) provides information to the patient and the family to make informed choices. Among the advanced Western countries and a few Asian countries, there are certified or trained professionals who perform GC. The Human Genome Project and next-generation sequencing diagnostics have provided an opportunity for increased genetic testing in the field of ophthalmology. The recent interventional therapeutic research strategies have also generated additional interest to seek GC globally, including in Asia. However, GC has several barriers to practise in the developing countries in Asia, namely, (a) shortage of qualified or trained genetic counsellors, (b) poor knowledge and reluctance in clinical adoption of genomics among the physicians in clinical practice, (c) overstretched public health services, and (d) negligible ophthalmic GC-related research and publications. The GC inadequacy in Asia is glaring in the most populous countries like China and India. Cultural differences, religious beliefs, misogyny, genetic discrimination, and a multitude of languages in Asia create unique challenges that counsellors in the West may only encounter with the immigrant minorities. Since there are currently 500 or more specific Mendelian genetic eye disorders, it is important for genetic counsellors to translate the genetic results at a level that the patient and family understand. There is therefore a need for governmental and healthcare organisations to train genetic counsellors in Asia and especially this practice must be included in the routine comprehensive ophthalmic care practice.

Revisiting benchmark study for response to methodological critiques of 'Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases'.

Evaluation of phenotype-driven gene prioritization approaches for Mendelian diseases could facilitate the software development and method selection for the workflow configuration and clinical practice. In our original article, the performance of 10 well-recognized causal-gene prioritization methods was benchmarked using 305 cases from the deciphering developmental disorders (DDD) project and 209 in-house cases via a relatively unbiased methodology. The evaluation results showed that LIRICAL and AMELIE were two of the best methods in our benchmark experiments, and the possible integrative approach of these two methods may enhance the diagnostic efficiency. However, some methodological critiques were raised by the authors of Exomiser and PhenIX, so we revisited our benchmarking studies to answer their comments in this letter.

PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations.

Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and the loss of function in proteins. The use of multiple sequence alignment alone-without considering the evolutionary relationships among sequences-results in the redundant counting of evolutionarily related alteration events, as if they were independent. Here, we propose a new method, PHACT, that predicts the pathogenicity of missense mutations directly from the phylogenetic tree of proteins. PHACT travels through the nodes of the phylogenetic tree and evaluates the deleteriousness of a substitution based on the probability differences of ancestral amino acids between neighboring nodes in the tree. Moreover, PHACT assigns weights to each node in the tree based on their distance to the query organism. For each potential amino acid substitution, the algorithm generates a score that is used to calculate the effect of substitution on protein function. To analyze the predictive performance of PHACT, we performed various experiments over the subsets of two datasets that include 3,023 proteins and 61,662 variants in total. The experiments demonstrated that our method outperformed the widely used pathogenicity prediction tools (i.e., SIFT and PolyPhen-2) and achieved a better predictive performance than other conventional statistical approaches presented in dbNSFP. The PHACT source code is available at https://github.com/CompGenomeLab/PHACT.

Clinical implementation of RNA sequencing for Mendelian disease diagnostics.

BACKGROUND: Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics. METHODS: We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease that previously underwent WES. We also assessed through simulations how aberrant expression and mono-allelic expression tests depend on RNA-seq coverage. RESULTS: We detected on average 12,500 genes per sample including around 60% of all disease genes-a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than 1 week from sample preparation to result reporting and provided a median of eight disease-associated genes per patient for inspection. A genetic diagnosis was established for 16% of the 205 WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions. CONCLUSION: Together, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics.

Frequency of carriers for rare metabolic diseases in a Brazilian cohort of 320 patients.

BACKGROUND: Several metabolic disorders follow an autosomal recessive inheritance pattern. Epidemiological information on these disorders is usually limited in developing countries. Our objective is to assess carrier frequencies of rare autosomal recessive metabolic diseases in a cohort of Brazilian patients that underwent molecular investigation with exome sequencing and estimate the overall frequency of these diseases using the Hardy-Weinberg equation. METHODS AND RESULTS: We reviewed the molecular findings of 320 symptomatic patients who had carrier status for recessive diseases actively searched. A total of 205 rare variants were reported in 138 different genes associated with metabolic diseases from 156 patients, which represents that almost half (48.8%) of the patients were carriers of at least one heterozygous pathogenic/likely pathogenic (P/LP) variant for rare metabolic disorders. Most of these variants are harbored by genes associated with multisystemic involvement. We estimated the overall frequency for rare recessive metabolic diseases to be 10.96/10,000 people, while the frequency of metabolic diseases potentially identified by newborn screening was estimated to be 2.93/10,000. CONCLUSIONS: This study shows the potential research utility of exome sequencing to determine carrier status for rare metabolic diseases, which may be a possible strategy to evaluate the clinical and social burden of these conditions at the population level and guide the optimization of health policies and newborn screening programs.

Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.

It's challenging work to identify disease-causing genes from the next-generation sequencing (NGS) data of patients with Mendelian disorders. To improve this situation, researchers have developed many phenotype-driven gene prioritization methods using a patient's genotype and phenotype information, or phenotype information only as input to rank the candidate's pathogenic genes. Evaluations of these ranking methods provide practitioners with convenience for choosing an appropriate tool for their workflows, but retrospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate. In this research, the performance of ten recognized causal-gene prioritization methods was benchmarked using 305 cases from the Deciphering Developmental Disorders (DDD) project and 209 in-house cases via a relatively unbiased methodology. The evaluation results show that methods using Human Phenotype Ontology (HPO) terms and Variant Call Format (VCF) files as input achieved better overall performance than those using phenotypic data alone. Besides, LIRICAL and AMELIE, two of the best methods in our benchmark experiments, complement each other in cases with the causal genes ranked highly, suggesting a possible integrative approach to further enhance the diagnostic efficiency. Our benchmarking provides valuable reference information to the computer-assisted rapid diagnosis in Mendelian diseases and sheds some light on the potential direction of future improvement on disease-causing gene prioritization methods.

Gene Hunting Approaches through the Combination of Linkage Analysis with Whole-Exome Sequencing in Mendelian Diseases: From Darwin to the Present Day.

BACKGROUND: In the context of medical genetics, gene hunting is the process of identifying and functionally characterizing genes or genetic variations that contribute to disease phenotypes. In this review, we would like to summarize gene hunting process in terms of historical aspects from Darwin to now. For this purpose, different approaches and recent developments will be detailed. SUMMARY: Linkage analysis and association studies are the most common methods in use for explaining the genetic background of hereditary diseases and disorders. Although linkage analysis is a relatively old approach, it is still a powerful method to detect disease-causing rare variants using family-based data, particularly for consanguineous marriages. As is known that, consanguineous marriages or endogamy poses a social problem in developing countries, however, this same condition also provides a unique opportunity for scientists to identify and characterize pathogenic variants. The rapid advancements in sequencing technologies and their parallel implementation together with linkage analyses now allow us to identify the candidate variants related to diseases in a relatively short time. Furthermore, we can now go one step further and functionally characterize the causative variant through in vitro and in vivo studies and unveil the variant-phenotype relationships on a molecular level more robustly. Key Messages: Herein, we suggest that the combined analysis of linkage and exome analysis is a powerful and precise tool to diagnose clinically rare and recessively inherited conditions.

Frequency of carriers for rare recessive Mendelian diseases in a Brazilian cohort of 320 patients.

Several Mendelian disorders follow an autosomal recessive inheritance pattern. Epidemiological information on many inherited disorders may be useful to guide health policies for rare diseases, but it is often inadequate, particularly in developing countries. We aimed to calculate the carrier frequencies of rare autosomal recessive Mendelian diseases in a cohort of Brazilian patients using whole exome sequencing (WES). We reviewed the molecular findings of WES from 320 symptomatic patients who had carrier status for recessive diseases. Using the Hardy-Weinberg equation, we estimated recessive disease frequencies (q2 ) considering the respective carrier frequencies (2pq) observed in our study. We calculated the sensitivity of carrier screening tests based on lists of genes from five different clinical laboratories that offer them in Brazil. A total of 425 occurrences of 351 rare variants were reported in 278 different genes from 230 patients (71.9%). Almost half (48.8%) were carriers of at least one heterozygous pathogenic/likely pathogenic variant for rare metabolic disorders, while 25.9% of epilepsy, 18.1% of intellectual disabilities, 15.6% of skeletal disorders, 10.9% immune disorders, and 9.1% of hearing loss. We estimated that an average of 67% of the variants would not have been detected by carrier screening panels. The combined frequencies of autosomal recessive diseases were estimated to be 26.39/10,000 (or ~0.26%). This study shows the potential research utility of WES to determine carrier status, which may be a possible strategy to evaluate the clinical and social burden of recessive diseases at the population level and guide the optimization of carrier screening panels.

PhenCards: a data resource linking human phenotype information to biomedical knowledge.

We present PhenCards ( https://phencards.org ), a database and web server intended as a one-stop shop for previously disconnected biomedical knowledge related to human clinical phenotypes. Users can query human phenotype terms or clinical notes. PhenCards obtains relevant disease/phenotype prevalence and co-occurrence, drug, procedural, pathway, literature, grant, and collaborator data. PhenCards recommends the most probable genetic diseases and candidate genes based on phenotype terms from clinical notes. PhenCards facilitates exploration of phenotype, e.g., which drugs cause or are prescribed for patient symptoms, which genes likely cause specific symptoms, and which comorbidities co-occur with phenotypes.

The Impact of Environmental Factors on Monogenic Mendelian Diseases.

Environmental factors and gene-environment interactions modify the variable expressivity, progression, severity, and onset of some classic (monogenic) Mendelian-inherited genetic diseases. Cystic fibrosis, Huntington disease, Parkinson's disease, and sickle cell disease are examples of well-known Mendelian disorders that are influenced by exogenous exposures. Environmental factors may act by direct or indirect mechanisms to modify disease severity, timing, and presentation, including through epigenomic influences, protein misfolding, miRNA alterations, transporter activity, and mitochondrial effects. Because pathological features of early-onset Mendelian diseases can mimic later onset complex diseases, we propose that studies of environmental exposure vulnerabilities using monogenic model systems of rare Mendelian diseases have high potential to provide insight into complex disease phenotypes arising from multi-genetic/multi-toxicant interactions. Mendelian disorders can be modeled by homologous mutations in animal model systems with strong recapitulation of human disease etiology and natural history, providing an important advantage for study of these diseases. Monogenic high penetrant mutations are ideal for toxicant challenge studies with a wide variety of environmental stressors, because background genetic variability may be less able to alter the relatively strong phenotype driving disease-causing mutations. These models promote mechanistic understandings of gene-environment interactions and biological pathways relevant to both Mendelian and related sporadic complex disease outcomes by creating a sensitized background for relevant environmental risk factors. Additionally, rare disease communities are motivated research participants, creating the potential of strong research allies among rare Mendelian disease advocacy groups and disease registries and providing a variety of translational opportunities that are under-utilized in genetic or environmental health science.

A novel statistical method for interpreting the pathogenicity of rare variants.

PURPOSE: To achieve the ultimate goal of personalized treatment of patients, accurate molecular diagnosis and precise interpretation of the impact of genetic variants on gene function is essential. With sequencing cost becoming increasingly affordable, the accurate distinguishing of benign from pathogenic variants becomes the major bottleneck. Although large normal population sequence databases have become a key resource in filtering benign variants, they are not effective at filtering extremely rare variants. METHODS: To address this challenge, we developed a novel statistical test by combining sequencing data from a patient cohort with a normal control population database. By comparing the expected and observed allele frequency in the patient cohort, variants that are likely benign can be identified. RESULTS: The performance of this new method is evaluated on both simulated and real data sets coupled with experimental validation. As a result, we demonstrate this new test is well powered to identify benign variants, and is particularly effective for variants with low frequency in the normal population. CONCLUSION: Overall, as a general test that can be applied to any type of variants in the context of all Mendelian diseases, our work provides a general framework for filtering benign variants with very low population allele frequency.